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The Immigration Office is one of the public service offices that has many activities carried out. These activities are often covered and published in the form of news articles. The news that has been published is very much making it difficult to find the desired news. One way to search is by ranking. Ranking is one branch of knowledge from information retrieval. Information retrieval is to find material (usually documents) from a collection of unstructured data (usually text) to meet the information needs of a large collection. One method of searching documents is to use Vector Space Model (VSM). VSM uses a concept found in linear algebra, namely vector space. Based on the concept used, document modeling was developed to search the required documents. Column vector representation is used in converting input documents. Another concept used is to know the closeness between two vectors, namely by calculating the amount of angle formed between two vectors and then sorted from data that has the smallest to the largest angles that indicate the order of ranking data from the most relevant to not relevant. One of the weighting algorithms is the tf-idf algorithm which is influenced by the frequency of occurrence of words in each online document and the frequency of online documents that have the word. In this study explained the visualization of VSM in searching documents on news about immigration in the East Nusa Tenggara region.